SIRT1 regulates Mxd1 during malignant melanoma progression

In a murine melanoma model, malignant transformation promoted by a sustained stress condition was causally related to increased levels of reactive oxygen species resulting in DNA damage and massive epigenetic alterations. Since the chromatin modifier Sirtuin-1 (SIRT1) is a protein attracted to double-stranded DNA break (DSB) sites and can recruit other components of the epigenetic machinery, we aimed to define the role of SIRT1 in melanomagenesis through our melanoma model. The DNA damage marker, gamma H2AX was found increased in melanocytes after 24 hours of deadhesion, accompanied by increased SIRT1 expression and decreased levels of its target, H4K16ac. Moreover, SIRT1 started to be associated to DNMT3B during the stress condition, and this complex was maintained along malignant progression. Mxd1 was identified by ChIP-seq among the DNA sequences differentially associated with SIRT1 during deadhesion and was shown to be a common target of both, SIRT1 and DNMT3B. In addition, Mxd1 was found downregulated from pre-malignant melanocytes to metastatic melanoma cells. Treatment with DNMT inhibitor 5AzaCdR reversed the Mxd1 expression. Sirt1 stable silencing increased Mxd1 mRNA expression and led to down-regulation of MYC targets, such as Cdkn1a, Bcl2 and Psen2, whose upregulation is associated with human melanoma aggressiveness and poor prognosis. We demonstrated a novel role of the stress responsive protein SIRT1 in malignant transformation of melanocytes associated with deadhesion. Mxd1 was identified as a new SIRT1 target gene. SIRT1 promoted Mxd1 silencing, which led to increased activity of MYC oncogene contributing to melanoma progression.FAPESP [2011/0166-38, 2011/12306-1, 2014/13663-0, 2015/07925-5, 2016/06488-3]DAAD [PKZ A/12/79134]FAPESP/BAYLAT [2012/51300-7]Univ Fed Sao Paulo UNIFESP, Dept Pharmacol, Ontogeny & Epigenet Lab, Sao Paulo, SP, BrazilUniv Sao Paulo, Ribeirao Preto Med Sch, Dept Genet, Ribeirao Preto, SP, BrazilFriedrich Alexander Univ Erlangen Nurnberg FAU, Inst Pathol, Expt Tumorpathol, Erlangen, GermanyFriedrich Alexander Univ Erlangen Nurnberg FAU, Dept Pediat & Adolescent Med, Erlangen, GermanyUniv Fed Sao Paulo UNIFESP, Dept Pharmacol, Ontogeny & Epigenet Lab, Sao Paulo, SP, BrazilFAPESP [2011/0166-38, 2011/12306-1, 2014/13663-0, 2015/07925-5, 2016/06488-3]DAAD [PKZ A/12/79134]FAPESP/BAYLAT [2012/51300-7]Web of Scienc

Epigenetic reprogramming as a key contributor to melanocyte malignant transformation

Melanoma progression requires deregulation of gene expression by currently uncharacterized epigenetic mechanisms. A mouse model based on changes in cell microenvironment was developed by our group to study melanocyte malignant transformation. Melanoma cell lines (4C11− and 4C11+) were obtained as result of 5 sequential anchorage blockades of non-tumorigenic melan-a melanocytes. Melan-a cells submitted to 4 de-adhesion cycles were also established (4C), are non-tumorigenic and represent an intermediary phase of tumor progression. The aim of this work was to identify factors contributing to epigenetic modifications in early and later phases of malignant transformation induced by anchorage impediment. Epigenetic alterations occur early in tumorigenesis; 4C cell line shows changes in global and gene-specific DNA methylation and histone marks. Many histone modifications differ between melan-a, 4C, 4C11− (non-metastatic melanoma cell line) and 4C11+ (metastatic melanoma cell line) which could be associated with changes in gene and microRNA expression. These epigenetic alterations seem to play a key role in malignant transformation since melanocytes treated with 5-Aza-2′-deoxycytidine before each anchorage blockade do not transform. Some epigenetic changes seem to be also responsible for the maintenance of malignant phenotype, since melanoma cell lines (4C11− and 4C11+) treated in vitro with 5-Aza-2′-deoxycytidine or Trichostatin A showed reduction of tumor growth in vivo. Changes in gene expression reflecting cell adaptation to new environment were also observed. We propose a model in which sustained microenvironmental stress in melanocytes results in epigenetic reprogramming. Thus, after adaptation, cells may acquire epigenetic marks that could contribute to the establishment of a malignant phenotype

Quantitative and enantioselective analyses of non-extractable residues of the fungicide metalaxyl in soil

Epigenetic modifications refer to a number of biological processes which alter the structure of chromatin and its transcriptional activity such as DNA methylation and histone post-translational processing. Studies have tried to elucidate how the viral genome and its products are affected by epigenetic modifications imposed by cell machinery and how it affects the ability of the virus to either, replicate and produce a viable progeny or be driven to latency. the purpose of this study was to evaluate epigenetic modifications in PBMCs and CD4(+) cells after HIV-1 infection analyzing three approaches: (i) global DNA-methylation; (ii) qPCR array and (iii) western blot. HIV-1 infection led to methylation increases in the cellular DNA regardless the activation status of PBMCs. the analysis of H3K9me3 and H3K27me3 suggested a trend towards transcriptional repression in activated cells after HIV-1 infection. Using a qPCR array, we detected genes related to epigenetic processes highly modulated in activated HIV-1 infected cells. SETDB2 and RSK2 transcripts showed highest up-regulation levels. SETDB2 signaling is related to transcriptional silencing while RSK2 is related to either silencing or activation of gene expression depending on the signaling pathway triggered down-stream. in addition, activated cells infected by HIV-1 showed lower CD69 expression and a decrease of IL-2, IFN-gamma and metabolism-related factors transcripts indicating a possible functional consequence towards global transcriptional repression found in HIV-1 infected cells. Conversely, based on epigenetic markers studied here, non-stimulated cells infected by HIV-1, showed signs of global transcriptional activation. Our results suggest that HIV-1 infection exerts epigenetic modulations in activated cells that may lead these cells to transcriptional repression with important functional consequences. Moreover, non-stimulated cells seem to increase gene transcription after HIV-1 infection. Based on these observations, it is possible to speculate that the outcome of viral infections may be influenced by the cellular activation status at the moment of infection

Scatter plot showing expression levels of the 84 genes encoding for enzymes related to epigenetic modifications.

<p>The diagram represents the relative expression levels calculated in log (2^-ΔΔCt) for each one of the 84 genes (blue dots). The data was generated using the RT² Profiler PCR Array Human Epigenetic Chromatin Modification Enzymes (PAHS-085A, SA Biosciences). The analysis was performed comparing the data from uninfected cells at 6, 12, 24 and 36h (x-axis) versus infected cells (y-axis) at 6, 12, 24 and 36h after infection. Pink lines delimit the zone of change in gene expression between −3 and +3 fold. The central axis (dark blue line) represents the mean normalized endogenous control expression. Dots above the pink lines correspond to up-regulated genes and bellow the line to down-regulated genes. Genes showing up-regulation ≥ +3 and down-regulation ≤ −3 are indicated in the plot.</p

Classical markers of epigenetic transcriptional silencing and activation in activated PBMCs after HIV-1 infection.

<p><b>(A)</b> Graphical representation of protein ratios of epigenetic transcriptional silencing marker H3K27me3 over the total H3. <b>(B)</b> Graphical representation of protein ratios of epigenetic transcriptional silencing marker and H3K9m3 over the total H3. <b>(C)</b> Graphical representation of protein ratios of epigenetic transcriptional activation marker H3K4m3 over the total H3. Protein levels of each marker were calculated by the ratio of band intensities between specific markers (H3K27me3, H3K9me3 or H3K4me3) over the total H3 (normalizer) using the software ImageJ v. 1.45s (Public domain, NIH, USA). Dark bars—HIV-1 infected cells; White bars—non-infected cells (control group). <b>(D)</b> Representative Western blot image for each epigenetic marker (H3K27me3—upper panel, H3K9me3—middle panel, H3K4me3—lower panel and the total H3 as normalizer. The data represent the mean of three different measurements of the same experiment and the error bars indicate the differences between two independent experiments. 2way ANOVA: *** p< 0.001, ** p < 0.01 and *, p < 0.05. (<b>NI</b>) non-infected cells, (<b>I</b>) HIV-1 infected cells.</p

Classical markers of epigenetic transcriptional silencing and activation of non-activated PBMCs at 24h after HIV-1 infection.

<p><b>(A)</b> Representative Western blot image for each epigenetic marker (H3K27me3—upper panel and H3K4me3—lower panel) and the total H3 as normalizer. <b>(B)</b> Graphical representation of protein ratios of epigenetic transcriptional silencing marker and H3K27m3 over the total H3. <b>(C)</b> Graphical representation of protein ratios of epigenetic transcriptional activation marker H3K4m3 over the total H3. Protein levels of each marker were calculated by the ratio of band intensities between specific markers (H3K27me3, H3K9me3 or H3K4me3) over the total H3 (normalizer) using the software ImageJ v. 1.45s (Public domain, NIH, USA). Dark bars—HIV-1 infected cells. <b>(D)</b> Percentage of 5’-methylcytosine content in genomic DNA. Data represent the mean of three different measurements of the same experiment and the error bars indicate the differences between two independent experiments. 2way ANOVA: *** p< 0.001, ** p < 0.01 and *, p < 0.05. <b>(E)</b> Flow cytometry of non-activated purified CD4⁺ T cells 36h post HIV-1 infection—dot plots of cell populations (gated on CD4⁺CD3⁺ cells) analyzed for the T cell early activation markers CD25, CD69 (percentages are shown in each quadrant) and graphical representation of the percentages of CD25⁺CD69⁺ cells (gated on CD4⁺CD3⁺ cells). Data are shown as mean ± SD of triplicates and are representative of three independent experiments using cells of three different healthy donors. Two-tailed Student’s t-test: *, p < 0.05. Dark bars—HIV-1 infected cells, White bars—non-infected cells, NA—non-activated cells. (<b>NI</b>) non-infected cells, (<b>I</b>) HIV-1 infected cells.</p

Experimental design and global DNA Methylation levels in HIV-1 infected activated PBMCs.

<p><b>(A)</b> Schematic representation of the experimental design and conditions: PBMC from healthy donors were separated by Ficoll gradient (in some experiments CD4⁺ cells were purified by positive selection). Cell viability was accessed by Trypan Blue exclusion. Cells were cultivated with a poor medium (RPMI+0.1% Bovine Albumin) for 24h in order to minimize any undesired previous activation. Next, cells were washed and resuspended in RPMI (supplemented)+10%FBS and activation stimulus (PHA+IL2) was added (activated group) or left without activation stimulus (non-activated group). After 36 hours of stimulation, the purity and activation status of cells were checked by flow cytometry using common human CD4⁺ T cell activation markers (CD25, HLA-DR and CD69). Next, 2x10⁷ cells were infected with HIV at a MOI (multiplicity of infection) of 0.05. The infections were carried out during the indicated time intervals (6h, 12h, 24h or 36h). After infection periods, cells were harvested, washed with PBS and cellular pellets were submitted to genomic DNA and RNA and protein extraction. <b>(B) and (C)</b> Experimental duplicates of 36h time-point agarose gel electrophoresis of genomic DNA from PBMCs after digestion with restriction enzymes HpaII and MspI. Gels were stained with SybrSafe dye (1:10.000—Invitrogen). HPA II—genomic DNA digested with Hpa II; MSP I genomic DNA digested with Msp I; C- Non-digested genomic DNA (Control). (<b>NI</b>) DNA from non-infected cells, (<b>I</b>) DNA from HIV-1 infected cells. The images are a representative of an experimental duplicate in which the cells were collected at 36h after HIV-1 infection. The experiments were performed in biological duplicates. <b>(D)</b> Percentage of 5’-methylcytosine content in genomic DNA at different time points. Dark bars—HIV-1 infected cells; White bars—non-infected cells. The data represent the mean of three different measurements and the error bars indicate the differences between three independent experiments. 2way ANOVA: *** p< 0.001, ** p < 0.01 and *, p < 0.05.</p